Data
QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3905

QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3905

deactivated ARFF Publicly available Visibility: public Uploaded 16-07-2016 by Noureddin Sadawi
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This dataset contains QSAR data (from ChEMBL version 17) showing activity values (unit is pseudo-pCI50) of several compounds on drug target ChEMBL_ID: CHEMBL3905 (TID: 11842), and it has 919 rows and 69 features (not including molecule IDs and class feature: molecule_id and pXC50). The features represent Molecular Descriptors which were generated from SMILES strings. Missing value imputation was applied to this dataset (By choosing the Median). Feature selection was also applied.

71 features

pXC50 (target)numeric237 unique values
0 missing
molecule_id (row identifier)nominal919 unique values
0 missing
Eig07_AEA.bo.numeric546 unique values
0 missing
Eig09_AEA.dm.numeric584 unique values
0 missing
Chi0_EA.dm.numeric777 unique values
0 missing
Eta_betaPnumeric54 unique values
0 missing
Eta_FLnumeric800 unique values
0 missing
Eig06_EAnumeric554 unique values
0 missing
SM14_AEA.bo.numeric554 unique values
0 missing
ATS1mnumeric552 unique values
0 missing
XMODnumeric851 unique values
0 missing
Eig09_EA.ri.numeric549 unique values
0 missing
Eig07_AEA.dm.numeric602 unique values
0 missing
MWnumeric782 unique values
0 missing
Eig07_EA.ri.numeric605 unique values
0 missing
Chi1_EA.dm.numeric804 unique values
0 missing
Eig06_AEA.ri.numeric616 unique values
0 missing
UNIPnumeric220 unique values
0 missing
IDETnumeric804 unique values
0 missing
Xunumeric794 unique values
0 missing
P_VSA_m_2numeric831 unique values
0 missing
LPRSnumeric807 unique values
0 missing
IDMTnumeric805 unique values
0 missing
SM04_EA.bo.numeric526 unique values
0 missing
IDDMnumeric345 unique values
0 missing
SMTInumeric799 unique values
0 missing
Eig10_EA.bo.numeric549 unique values
0 missing
SpMax8_Bh.v.numeric458 unique values
0 missing
SM04_AEA.bo.numeric507 unique values
0 missing
GMTInumeric794 unique values
0 missing
Eig15_AEA.dm.numeric620 unique values
0 missing
VvdwZAZnumeric811 unique values
0 missing
IDEnumeric594 unique values
0 missing
Uinumeric29 unique values
0 missing
MSDnumeric744 unique values
0 missing
SpMax8_Bh.p.numeric450 unique values
0 missing
S1Knumeric685 unique values
0 missing
CSInumeric580 unique values
0 missing
ECCnumeric433 unique values
0 missing
nSKnumeric36 unique values
0 missing
nBMnumeric29 unique values
0 missing
Ucnumeric29 unique values
0 missing
SpAD_EA.ed.numeric804 unique values
0 missing
ZM2Pernumeric874 unique values
0 missing
SpMaxA_AEA.bo.numeric165 unique values
0 missing
Eig12_EA.bo.numeric573 unique values
0 missing
Eig11_AEA.dm.numeric542 unique values
0 missing
SpMax5_Bh.m.numeric522 unique values
0 missing
Dznumeric265 unique values
0 missing
DECCnumeric620 unique values
0 missing
GMTIVnumeric882 unique values
0 missing
SM02_AEA.ed.numeric196 unique values
0 missing
ATSC5mnumeric899 unique values
0 missing
ON0numeric166 unique values
0 missing
MDDDnumeric781 unique values
0 missing
ATS1snumeric557 unique values
0 missing
Vindexnumeric206 unique values
0 missing
GGI9numeric349 unique values
0 missing
SpMax5_Bh.e.numeric489 unique values
0 missing
Psi_e_1numeric795 unique values
0 missing
SpMin6_Bh.v.numeric441 unique values
0 missing
Eig12_AEA.dm.numeric554 unique values
0 missing
piPC04numeric538 unique values
0 missing
MPC05numeric140 unique values
0 missing
SM03_AEA.ed.numeric507 unique values
0 missing
Eig12_EAnumeric520 unique values
0 missing
SM06_AEA.dm.numeric520 unique values
0 missing
SRW10numeric545 unique values
0 missing
Ramnumeric19 unique values
0 missing
ATSC4inumeric702 unique values
0 missing
Eig06_AEA.dm.numeric605 unique values
0 missing

62 properties

919
Number of instances (rows) of the dataset.
71
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
70
Number of numeric attributes.
1
Number of nominal attributes.
Entropy of the target attribute values.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Second quartile (Median) of entropy among attributes.
0.08
Number of attributes divided by the number of instances.
Average number of distinct values among the attributes of the nominal type.
0.04
Second quartile (Median) of kurtosis among attributes of the numeric type.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
-0.01
Mean skewness among attributes of the numeric type.
5.76
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
932.4
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
-0.03
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-0.56
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.7
Second quartile (Median) of standard deviation of attributes of the numeric type.
5.96
Maximum kurtosis among attributes of the numeric type.
0.15
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
39011.99
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
0.96
Third quartile of kurtosis among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
The minimal number of distinct values among attributes of the nominal type.
98.59
Percentage of numeric attributes.
30.19
Third quartile of means among attributes of the numeric type.
The maximum number of distinct values among attributes of the nominal type.
-1.51
Minimum skewness among attributes of the numeric type.
1.41
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
1.8
Maximum skewness among attributes of the numeric type.
0.04
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
0.41
Third quartile of skewness among attributes of the numeric type.
25770.1
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
-0.16
First quartile of kurtosis among attributes of the numeric type.
15.06
Third quartile of standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
1.95
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
0.62
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
1384.19
Mean of means among attributes of the numeric type.
-0.53
First quartile of skewness among attributes of the numeric type.
0.2
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.31
First quartile of standard deviation of attributes of the numeric type.

12 tasks

2 runs - estimation_procedure: Custom 10-fold Crossvalidation - target_feature: pXC50
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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